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newsletter-signal-scanner时事通讯信号扫描仪

Agent Skill

newsletter-signal-scanner 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

196

周安装

8

GitHub Stars

630

下载量

63
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:newsletter-signal-scanner(时事通讯信号扫描仪)
来源仓库:https://github.com/gooseworks-ai/goose-skills
仓库路径:skills/newsletter-signal-scanner
安装命令:
npx skills add https://github.com/gooseworks-ai/goose-skills --skill newsletter-signal-scanner
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/gooseworks-ai/goose-skills --skill newsletter-signal-scanner

简介

newsletter-signal-scanner 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • 适用于新闻聚合、信息检索、内容筛选等研究检索类任务场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和联网需求。
  • 安装前建议核实维护状态、是否会触发命令执行或文件读写操作。
  • 可结合原始 README 文档进一步核验具体功能和使用方法。

SKILL.md

Newsletter Signal Scanner

Turn your newsletter subscriptions into a structured intelligence feed. Monitors an AgentMail inbox for incoming newsletters, extracts signal-relevant content by keyword campaign, and delivers a weekly digest of what matters — competitor mentions, ICP pain language, market shifts, and emerging topics.

When to Use

  • "Monitor industry newsletters for competitor mentions"
  • "Alert me when newsletters mention [topic] or [company]"
  • "What are newsletters writing about this week in our space?"
  • "Set up newsletter monitoring for [client]"

Phase 0: Intake

Newsletters to Monitor

  1. Which newsletters should be subscribed to and monitored? (List names or URLs)

- If unknown, ask: "What 3-5 newsletters does your ICP read?" — then use sponsored-newsletter-finder to discover others.

  1. Which AgentMail inbox should receive them? (Or should we create a new one?)

Keyword Campaigns

  1. Competitor names to track (e.g., "Clay", "Apollo", "Outreach")
  2. ICP pain-language terms to track (e.g., "outbound struggling", "pipeline dried up", "SDR ramp")
  3. Market shift terms (e.g., "AI SDR", "agent-led growth", "GTM engineer")
  4. Your brand name (to catch mentions)

Output

  1. Digest delivery: Slack channel, email, or markdown file? (default: markdown file)
  2. Frequency: daily or weekly? (default: weekly)

Save campaign config to the current working directory as newsletter-signals.json (or user-specified path).

{
  "inbox_id": "<agentmail_inbox_id>",
  "keyword_campaigns": {
    "competitors": ["Clay", "Apollo", "Outreach", "Salesloft"],
    "pain_language": ["pipeline is down", "outbound isn't working", "SDR ramp"],
    "market_shifts": ["AI SDR", "GTM engineer", "agent-led"],
    "brand_mentions": ["YourCompany", "yourcompany.com"]
  },
  "newsletters": [
    {"name": "Exit Five", "from_domain": "exitfive.com"},
    {"name": "The GTM Newsletter", "from_domain": "gtmnewsletter.com"}
  ],
  "output": {
    "format": "markdown",
    "path": "newsletter-signals-[DATE].md"
  }
}

Phase 1: Scan Inbox

Use the AgentMail API (agentmail.dev) to fetch new emails from the monitored inbox:

Fetch emails from inbox <inbox_id> since <last_scan_date>
Filter to: known newsletter senders (match against newsletters config)

For each email:

  • Extract subject, sender, date, full body text
  • Strip HTML → plain text for analysis

Phase 2: Apply Keyword Campaigns

For each newsletter email, scan for keyword matches:

for email in emails:
    matches = {}
    for campaign, keywords in keyword_campaigns.items():
        found = []
        for keyword in keywords:
            if keyword.lower() in email.body.lower():
                # Extract context: 50 chars before + keyword + 50 chars after
                context = extract_context(email.body, keyword)
                found.append({"keyword": keyword, "context": context})
        if found:
            matches[campaign] = found
    email.signal_matches = matches

Only include emails with at least one keyword match in the digest.

Phase 3: Extract Signal Snippets

For each matched email, extract clean signal snippets:

Competitor mention example:

Newsletter: The GTM Newsletter | Date: 2026-03-05 Campaign: competitors Keyword: "Clay" Context: "...teams that use Clay for enrichment are seeing 3x better personalization rates compared to..."

Pain language example:

Newsletter: Exit Five | Date: 2026-03-04 Campaign: pain_language Keyword: "outbound isn't working" Context: "...a lot of founders telling me outbound isn't working the way it used to. The reply rates I'm seeing..."

Phase 4: Output Format

# Newsletter Signal Digest — Week of [DATE]

## Summary
- Newsletters scanned: [N]
- Emails with signals: [N]
- Top trending topic: [topic]

---

## Competitor Mentions

### Clay
- **[Newsletter Name]** — [Date]
  > "[Context snippet]"
  Source: [email subject] | [URL if available]

### [Other Competitor]
...

---

## ICP Pain Language

Signals suggesting your ICP is feeling pain your product solves:

- **[Newsletter Name]** — [Date]
  > "[Context snippet]"
  — Relevance: [why this matters]

---

## Market Shift Signals

Emerging topics gaining newsletter coverage:

- **"[Topic]"** — mentioned in [N] newsletters this week
  > "[Context snippet]"

---

## Your Brand Mentions
[Any mentions of your company or product]

---

## Recommended Actions
1. [Specific action based on signals — e.g., "Exit Five is covering AI SDR fatigue — good moment to publish our take"]
2. [Competitive response if needed]

Save to the current working directory as newsletter-signals-[YYYY-MM-DD].md (or user-specified path).

Phase 5: Setup — Subscribe to Newsletters

For first-time setup, subscribe the AgentMail address to target newsletters:

  1. Get the AgentMail inbox address (via AgentMail API at agentmail.dev)
  2. For each newsletter, visit subscription page and submit the AgentMail address
  3. Confirm subscriptions (check inbox for confirmation emails)
  4. Allow 1-2 weeks of accumulation before first full digest

Scheduling

Run weekly (Monday morning recommended):

# Every Monday at 7am — before the team's standup
0 7 * * 1 python3 run_skill.py newsletter-signal-scanner --client <client-name>

Cost

ComponentCost
AgentMail inboxDepends on AgentMail pricing
Email parsing + keyword matchingFree (local logic)
TotalNear-zero ongoing cost

Tools Required

  • AgentMail API (agentmail.dev) — for inbox access. Requires AGENTMAIL_API_KEY environment variable and the agentmail pip package (pip3 install agentmail).

Trigger Phrases

  • "Scan newsletters for this week's signals"
  • "What are industry newsletters saying about [topic]?"
  • "Run newsletter signal scanner for [client]"
  • "Set up newsletter monitoring"

适合场景

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用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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能力 3

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

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按下载量换算21

Claude

29.47%
按下载量换算19

Cursor

18.04%
按下载量换算11

Gemini CLI

10.32%
按下载量换算7

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安装前确认

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